mlpois: Poisson distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Poisson distribution maximum likelihood estimation

Description

The maximum likelihood estimate of lambda is the empirical mean.

Usage

mlpois(x, na.rm = FALSE, ...)

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
...	currently affects nothing.

Details

For the density function of the Poisson distribution see Poisson.

Value

mlpois returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for lambda and the following attributes:

model	The name of the model.
density	The density associated with the estimates.
logLik	The loglikelihood at the maximum.
support	The support of the density.
n	The number of observations.
call	The call as captured my match.call

References

Johnson, N. L., Kemp, A. W., & Kotz, S. (2005). Univariate Discrete Distributions (3rd ed.). Wiley-Blackwell.

See Also

Poisson for the Poisson density.

Examples

mlpois(ChickWeight$weight)

univariateML documentation built on April 3, 2025, 11:09 p.m.